The mutationathon highlights the importance of reaching standardization in estimates of pedigree-based germline mutation rates
Abstract
In the past decade, several studies have estimated the human per-generation germline mutation rate using large pedigrees. More recently, estimates for various non-human species have been published. However, methodological differences among studies in detecting germline mutations and estimating mutation rates make direct comparisons difficult. Here, we describe the many different steps involved in estimating pedigree-based mutation rates, including sampling, sequencing, mapping, variant calling, filtering, and how to appropriately account for false-positive and false-negative rates. For each step, we review the different methods and parameter choices that have been used in the recent literature. Additionally, we present the results from a 'Mutationathon', a competition organized among five research labs to compare germline mutation rate estimates for a single pedigree of rhesus macaques. We report almost a two-fold variation in the final estimated rate among groups using different post-alignment processing, calling, and filtering criteria and provide details into the sources of variation across studies. Though the difference among estimates is not statistically significant, this discrepancy emphasizes the need for standardized methods in mutation rate estimations and the difficulty in comparing rates from different studies. Finally, this work aims to provide guidelines for computational and statistical benchmarks for future studies interested in identifying germline mutations from pedigrees.
Data availability
The sequences of the pedigree analyzed are available on NCBI under the accession numbers:SRR10426295;SRR10426294;SRR10426275;SRR10426264;SRR10426253;SRR10426291;SRR10426290;SRR10426256;SRR10426255.The PCR experiment and Sanger resequencing produced for this work are deposited on Genbank under the accession number MZ661796 - MZ662076. Supplementary table 4 describe the data.The scripts used by the participants of the Mutationathon are publically available on different github described in the manuscript.Figure 3, 4 and 5 can be reproduced with the data in Figure 3 - source data 1, Figure 4 - source data 1, and Figure 5 - source data 1 .
Article and author information
Author details
Funding
Carlsbergfondet (CF16-0663)
- Guojie Zhang
US national science foundation CAREER (DEB-2045343)
- Susanne P Pfeifer
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Copyright
© 2022, Bergeron et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
Metrics
-
- 3,577
- views
-
- 397
- downloads
-
- 52
- citations
Views, downloads and citations are aggregated across all versions of this paper published by eLife.
Citations by DOI
-
- 52
- citations for umbrella DOI https://doi.org/10.7554/eLife.73577